repetitive analysis

I want to process data contained in a table according to the example attached. The table consists in 100 columns + one column serving as a control measure, and with 30 to 80 rows.

The aim is to apply a statistical test in an iterative manner starting with control vs column 51, control vs column 52, control vs column 53, etc… in order to detect when a significant difference appears, how long it is present on successive columns and when the significance is lost.

For example, a difference can be detected from column 63 to column 78, and then lost from c79 to c86, and then reappears on c87 to c98.

I don't know how I can write a script which allows an automatic analysis of this type of table, giving a report of the moments at which differences occur.

Re: repetitive analysis

Feb 27, 2015 8:49 AM(1547 views)

Hi Paul,

thank you, that helped a lot.

It seems that scripting is not mandatory here. You could do the following:

1. Tables > Stack: Get a new data table with data from your control column and all measurement columns stacked. This will create a column Label with your column names, and a second column with your all your data.

The attached file shows my result.

2. Analyse > Fit Y by X, with X=Label and Y=Data > Hotspot > Compare Means > With Control, Dunnett's: Choose your control column and you will get all pairwise tests. You can right-click the table under LSD Threshold Matrix, e.g. to sort it or to make it into a data table (maybe for graphing p-values in Graph Builder).

Re: repetitive analysis

Someone should probably mention that the approach y'all are taking might cause a sizable number of dead preeminent statisticians to spin like lathes in their respective graves.

I cannot discern exactly what decision you're trying to make from your description, but it sounds more like changepoint detection to me. If so, analyzing a number of sequentially-aggregated p-values from any two-sample test could be considered poor form at best.

Re: repetitive analysis

Feb 27, 2015 1:04 PM(1547 views)

Thanks Kevin, any suggestion is appreciated.

From my understanding Paul did not choose any test yet, but was more asking for a way how to run a sequence of two-sample tests (one sample always the same) in JMP, given his original data set. My point was that scripting would not be necessary in this case.

Re: repetitive analysis

Without more information, I'm not doing much more than shooting in the dark.

But if, as I suspect, you are searching through sequentially-gathered data in an attempt to discern a change in the data's generative process, a changepoint approach might be more justified.

There are many ways to detect changepoints, and a rich trove of references going back many years.

CRAN has a changepoint package that implements several recently-researched methods in R. JMP has some neat R integration, in which you can execute R code on JMP datasets and get the results back into JMP. Try the Pruned Exact Linear Time (PELT) method referenced in R. Killick , P. Fearnhead & I. A. Eckley (2012) Optimal Detection of Changepoints With a Linear Computational Cost, Journal of the American Statistical Association, 107:500, 1590-1598.

Re: repetitive analysis

Feb 27, 2015 1:58 PM(1547 views)

That’s a constructive way to exchange advice ! Thanks for that Kevin. It is interesting to know that we can go back and forth with R and JMP. I will surely take a closer look to changepoint procedures.